An improved fourier method for power system frequency estimation

Power system frequency is a critical parameter of voltage and current measurements for many applications such as power quality, monitoring and protection. This paper presents a new approach for frequency estimation based on Taylor series expansion and Fourier algorithm. The method is derived using a dynamic signal model with varying parameters. The changing envelope of a power signal within an observation data window is approximated with a second order Taylor series. Fourier algorithm is used for computing the parameters of such signal model. The algorithm using linear model approach is presented as well to alleviate the computational complexity. Inheriting from Fourier algorithm, this algorithm is immune to power system harmonics. It achieves excellent performance for signals with dynamic variations. The performance is investigated and compared with other techniques through simulations for various scenarios observed in real power system. Experimental studies demonstrate the advantages of the proposed algorithm.